Advances in technology have increased the number of avenues for traders to invest in stocks, bonds, futures, convertible securities, commodities and other tradeable elements in markets worldwide. This trend has also increased the need for delivery of timely trading data to investors. It is now commonplace for traders to access market analysis tools electronically via e-mail or website access.
Many technical analysis tools focus on price as the key market indicator. For example, tools based on moving averages of securities prices are well-known. However, an equally important factor that is often overlooked is market volume. Volume represents the actual supply and demand that moves prices higher and lower. Volume is therefore an important indicator that can offer key insights into the strength of a market trend.
Volume analytics can be employed, for example, to forecast reversals in stock exchange indices. In the case of a securities index, sudden surges in trading volume indicate bursts of significant buying or selling activity. There are many complex reasons why this might occur. If the index price trend is rising when a volume surge occurs, this is typically referred to as a “resistive” volume spike. On the other hand, if the index price trend is declining when the volume surge occurs, this is referred to as a “supportive” volume spike. As a general rule, resistive volume spikes will force a downward move in an index whereas supportive volume spikes generate upward index momentum.
However, it is often very difficult using conventional market analysis tools to identify volume fluctuations which are truly significant. Many currently available systems are limited to delivering daily delayed data and fail to take into account volume fluctuations which occur at intervals within the trading period. In many cases volume activity follows predictable patterns throughout the trading day. High volume levels are usually prevalent immediately after the markets open due to trades left over from the previous day and a large amount of at-market-open orders. Lower values occur around noon when traders typically take their lunch break, thereby lowering the number of active participants in the market. Increased volume levels once again occur toward the end of the trading day when many short-term traders and institutional investors close their positions. Thus the time of the day often has a direct influence on volume activity. It is therefore often difficult to differentiate abnormal, analytically significant volume fluctuations from historically normal intra-day variations.
Some systems are known in the prior art for attempting to normalize volume data so that at least some cyclic intra-day fluctuations are discounted and abnormal volume variations can be more readily visualized. For example, as described further below, some systems rely on standard trade distribution profiles which are intended to approximate typical market activity patterns. There are several significant drawbacks to this approach. First, not all markets for tradeable elements will exhibit the standard profile. Second, even in the case of tradeable elements which ordinarily do track the standard profile, important deviations may occur at some trading intervals due to various extraneous factors. In such cases, the normalized data may obscure important volume spikes or suggest market abnormalities where none exist. Accordingly, in many cases conventional systems yield inaccurate results and cannot be applied generally to all market scenarios.
The need has therefore arisen for improved methods and systems for modulating volume information which rely on actual historical volume data for the tradeable element in question rather than imprecise trade distribution profiles.